Cost and Time-Cost Effectiveness of Multiprocessing

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17 Scopus citations


Speedup and efficiency are two measures for performance of pipelined computers. Now, these measures are used to evaluate performance of parallel algorithms for multiprocessor systems. However, to evaluate the performance of a parallel algorithm, these measures consider only the computation time and number of processors used, but do not include the number of the communication links in the system. In this paper, we define two new measures, cost effectiveness and time-cost effectiveness, for evaluating performance of a parallel algorithm for a multiprocessor system. From these two measures we define two characterization factors for multiprocessor systems. We use these new characterizing factors to analyze some well-known multiprocessor systems. It is found that for a given penalty function, every multiprocessor architecture has an optimal number of processors that produces maximum profit. If “too many” processors are used, the higher cost of the system reduces the profit obtained from the faster solution. On the other hand, if “too few” processors are used, the penalty paid for taking a longer time to obtain the solution reduces the profit.

Original languageEnglish (US)
Pages (from-to)704-712
Number of pages9
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number6
StatePublished - Jun 1993


  • Cost effectiveness
  • efficiency
  • hypercubes
  • interconnection networks
  • mesh-connected computers
  • multiprocessing
  • parallel algorithms
  • speedup

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics


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